feat(components): SageMaker V2 model monitor component release (#9368)
* Generate using updated generator * Update license version * Update container image version * Update Changelog.md * Update changelog * Update Changelog.md
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rd-pong
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@ -4,6 +4,14 @@ The version of the AWS SageMaker Components is determined by the docker image ta
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Repository: [Public ECR](https://gallery.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components) or [Dockerhub](https://hub.docker.com/repository/docker/amazon/aws-sagemaker-kfp-components). New releases after v1.1.1 will be using the public ECR repository
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---------------------------------------------
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** Change log for version 2.3.0 **
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- Introducing SageMaker Model Monitor components v2. This release includes [Monitoring Schedule](./MonitoringSchedule/), [DataQualityJobDefinition](./DataQualityJobDefinition/), [ModelQualityJobDefinition](./ModelQualityJobDefinition/), [ModelExplainabilityJobDefinition](./ModelExplainabilityJobDefinition/), [ModelBiasJobDefinition](./ModelBiasJobDefinition/).
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> Pull request : [#9253](https://github.com/kubeflow/pipelines/pull/9253), [#9368](https://github.com/kubeflow/pipelines/pull/9368)
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Note: [#9253](https://github.com/kubeflow/pipelines/pull/9253) was merged accidentally with image pointing to an unofficial repository. Please do not pin to the commit corresponding to this PR.
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** Change log for version 2.2.1 **
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- Fix: Path issue with git clone on macbook. Directory name for version 2 of Model component has been updated from `components/aws/sagemaker/Model` to `components/aws/sagemaker/Modelv2`.
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> Pull request : [#9331](https://github.com/kubeflow/pipelines/pull/9331)
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@ -92,7 +92,7 @@ outputs:
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implementation:
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container:
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image: rdpen/test-modelmoni:31
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- DataQualityJobDefinition/src/DataQualityJobDefinition_component.py
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@ -86,7 +86,7 @@ outputs:
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implementation:
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container:
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.2.1
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- Endpoint/src/Endpoint_component.py
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@ -44,8 +44,8 @@ class SageMakerEndpointComponent(SageMakerComponent):
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############GENERATED SECTION BELOW############
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self.job_name = spec.inputs.endpoint_name = (
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spec.inputs.endpoint_name # todo: need customize
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if spec.inputs.endpoint_name # todo: need customize
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spec.inputs.endpoint_name
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if spec.inputs.endpoint_name
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else SageMakerComponent._generate_unique_timestamped_id(prefix="endpoint")
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)
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@ -68,7 +68,7 @@ outputs:
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implementation:
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container:
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.2.1
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- EndpointConfig/src/EndpointConfig_component.py
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@ -44,8 +44,8 @@ class SageMakerEndpointConfigComponent(SageMakerComponent):
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############GENERATED SECTION BELOW############
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self.job_name = spec.inputs.endpoint_config_name = (
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spec.inputs.endpoint_config_name # todo: need customize
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if spec.inputs.endpoint_config_name # todo: need customize
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spec.inputs.endpoint_config_name
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if spec.inputs.endpoint_config_name
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else SageMakerComponent._generate_unique_timestamped_id(
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prefix="endpoint-config"
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)
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@ -92,7 +92,7 @@ outputs:
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implementation:
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container:
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image: rdpen/test-modelmoni:31
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- ModelBiasJobDefinition/src/ModelBiasJobDefinition_component.py
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@ -92,7 +92,7 @@ outputs:
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implementation:
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container:
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image: rdpen/test-modelmoni:31
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- ModelExplainabilityJobDefinition/src/ModelExplainabilityJobDefinition_component.py
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@ -92,7 +92,7 @@ outputs:
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implementation:
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container:
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image: rdpen/test-modelmoni:31
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- ModelQualityJobDefinition/src/ModelQualityJobDefinition_component.py
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@ -80,7 +80,7 @@ outputs:
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implementation:
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container:
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.2.1
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- Modelv2/src/Model_component.py
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@ -44,8 +44,8 @@ class SageMakerModelComponent(SageMakerComponent):
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############GENERATED SECTION BELOW############
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self.job_name = spec.inputs.model_name = (
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spec.inputs.model_name # todo: need customize
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if spec.inputs.model_name # todo: need customize
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spec.inputs.model_name
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if spec.inputs.model_name
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else SageMakerComponent._generate_unique_timestamped_id(prefix="model")
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)
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@ -75,7 +75,7 @@ outputs:
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implementation:
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container:
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image: rdpen/test-modelmoni:31
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- MonitoringSchedule/src/MonitoringSchedule_component.py
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@ -1,4 +1,4 @@
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** Amazon SageMaker Components for Kubeflow Pipelines; version 2.2.1 --
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** Amazon SageMaker Components for Kubeflow Pipelines; version 2.3.0 --
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https://github.com/kubeflow/pipelines/tree/master/components/aws/sagemaker
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Copyright 2022 Amazon.com, Inc. or its affiliates. All Rights Reserved.
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** pathlib2; version 2.3.5 --
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@ -209,7 +209,7 @@ outputs:
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implementation:
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container:
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.2.1
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image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:2.3.0
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command: [python3]
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args:
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- TrainingJob/src/TrainingJob_component.py
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@ -44,8 +44,8 @@ class SageMakerTrainingJobComponent(SageMakerComponent):
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############GENERATED SECTION BELOW############
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self.job_name = spec.inputs.training_job_name = (
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spec.inputs.training_job_name # todo: need customize
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if spec.inputs.training_job_name # todo: need customize
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spec.inputs.training_job_name
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if spec.inputs.training_job_name
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else SageMakerComponent._generate_unique_timestamped_id(
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prefix="training-job"
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)
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